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1. 负责ADAS真值系统的感知软件系统设计与研发。
   Responsible for ADAS ground truth system perception software system design and development.
2. 负责ADAS真值系统的融合检测分割算法的训练、部署与开发。 熟悉主流的基于激光雷达和摄像头的动静态AI模型。E2E模型知识和经验是加分项。
   Responsible for ADAS ground truth system multi-sensor fusion detection and segmentation algorithm design, training, and deployment. Familiar with popular lidar/camera-based dynamic and static perception AI models. E2E model knowledge and experience are a plus.
3. 负责ADAS真值系统的跟踪算法的训练、部署与开发。
   Responsible for ADAS ground truth system multi-sensor fusion tracking algorithm training, deployment and development.
4. 负责ADAS真值系统云端数据管道与处理流程的开发。
   Responsible for ADAS ground truth system cloud pipeline system design and development.
5. 协助ADAS真值系统的车载传感器硬件方案制定与采集系统集成。
   Support for ADAS ground truth system data acquisition system integration.
6. 与其他团队配合，分析和挖掘极端情况、表征原因、内在规律等，例如自动驾驶功能潜在风险与事故的数据分析与规律等。
   Cooperate with other teams to analyze corner cases, characterization causes, and internal laws of the automatic driving function, such as data analysis and patterns of potential risks and accidents.

1. 数学、机器学习、计算机、机器人等相关专业，并且在计算机视觉/感知算法等领域有3年以上工作经验。
   Minimum of a Master's Degree in Mathematics, Machine Learning, Computer Science, Robotics or related fields, with 3+ years of experience in deep learning, machine learning, or computer vision.
2. 熟练掌握编程技能且有实践经验，例如 C, C++, Python。
   Proficiency and practical experience in programming, e.g., C, C++, Python.
3. 熟练掌握深度学习编程框架，例如 PyTorch、TensorFlow 等。
   Proficiency and practical experience in deep learning frameworks such as PyTorch, TensorFlow.
4. 熟练掌握融合跟踪算法的预处理、运动模型、距离量测、匹配规则、生命周期等。
   Proficiency and practical experience in multi-sensor fusion tracking algorithms, including pre-processing, motion models, measurement models, data association, matching strategies, and lifecycle management.
5. 在感知结果数据挖掘、感知算法迁移与设计有一定经验。
   Experience in perception data mining, algorithm adaptation, and design.
6. 具备 vibe coding 能力：能够熟练使用大语言模型（LLM）独立开发工具、脚本和自动化流程，快速验证想法并提升开发效率。
   Vibe coding capability: Demonstrated ability to leverage Large Language Models (LLMs) to independently develop tools, scripts, and automation workflows for rapid prototyping and productivity enhancement.
7. 思维活跃，学习能力强，善于探索未知领域。
   Active thinking, strong learning ability, and enthusiasm for exploring unknown areas.
8. 具有自主和高效的工作方式的强大的团队成员。
   Strong team player with an autonomous and efficient working style.
9. 具有出色的沟通技巧，流畅的英语表述（口头和书面）。
   Excellent communication skills, fluent in English (oral and written).
10. 具有创新、问题解决的热情 & 创业性心态。
    Passion for innovation, problem solving & entrepreneurial mindset.

加分项

1. 熟悉 DevOps 工具使用，例如 Git、Docker、Airflow、K8s 等。
   Familiarity with DevOps tools, e.g., Git, Docker, Airflow, Kubernetes.
2. 曾在领域内的顶级会议发表论文（例如：ICRA、IROS）。
   Published and presented at top conferences in related fields, e.g., ICRA, IROS.
3. 有出色的感知算法产品及落地经验。
   Excellent experience in perception algorithm products and implementation.